Siddhartha Srinivasa
Carnegie Mellon University, Robotics Institute, Faculty Member
- I am the Boeing Endowed Professor at the Paul G. Allen School of Computer Scienceedit
This technical report presents an anytime algorithm for solving the multi-robot guaranteed search problem. Guaranteed search requires a team of robots to clear an environment of a po- tentially adversarial target. In other words, a team... more
This technical report presents an anytime algorithm for solving the multi-robot guaranteed search problem. Guaranteed search requires a team of robots to clear an environment of a po- tentially adversarial target. In other words, a team of searchers must generate a search strategy guaranteed to flnd a target. This problem is known to be NP-complete on arbitrary graphs but
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
We present an efficient approach to generating paths for humanoids and other robotic manipulators that uses the Task Space Region (TSR) framework to specify manipulation tasks. TSRs can define acceptable goal poses of an end-effector or... more
We present an efficient approach to generating paths for humanoids and other robotic manipulators that uses the Task Space Region (TSR) framework to specify manipulation tasks. TSRs can define acceptable goal poses of an end-effector or constraints on the end-effector's pose during the path, or both. First presented as a method for goal-specification, TSRs are a straightforward representation of sets
Research Interests:
ABSTRACT In human relationships, responsiveness---behaving in a sensitive manner that is supportive of another person's needs---plays a major role in any interaction that involves effective communication, caregiving, and social... more
ABSTRACT In human relationships, responsiveness---behaving in a sensitive manner that is supportive of another person's needs---plays a major role in any interaction that involves effective communication, caregiving, and social support. Perceiving one's partner ...
ABSTRACT How should a human user and a robot collaborate during teleoperation? The user understands the full semantics of the task: they know, for example, what the robot should search for in a cupboard, or that it should be more careful... more
ABSTRACT How should a human user and a robot collaborate during teleoperation? The user understands the full semantics of the task: they know, for example, what the robot should search for in a cupboard, or that it should be more careful when moving near a glass of water than near a box of tissues. Since the robot might not have this knowledge, allowing it to operate fully autonomously may be risky; its model is incomplete and its policy might be wrong. On the other hand, teleoperating the robot through every motion is slow and tiresome, especially on difficult tasks. Between these two extremes lies a spectrum, from almost no assistance at all (very timid) to full autonomy (very aggressive). So what is the appropriate level of assistance? And how do factors like task difficulty and policy correctness affect this decision?
Research Interests:
Research Interests:
We present a manipulation planning framework that allows robots to plan in the presence of constraints on end-effector pose, as well as other common constraints. The framework has three main components: constraint representation,... more
We present a manipulation planning framework that allows robots to plan in the presence of constraints on end-effector pose, as well as other common constraints. The framework has three main components: constraint representation, constraint-satisfaction strategies, and a general planning algorithm. These components come together to create an efficient and probabilistically complete manipulation planning algorithm called the Constrained BiDirectional Rapidly-exploring Random
Research Interests:
ABSTRACT In assistive teleoperation, the robot helps the user accomplish the desired task, making teleoperation easier and more seamless. Rather than simply executing the user's input, which is hindered by the inadequacies of the... more
ABSTRACT In assistive teleoperation, the robot helps the user accomplish the desired task, making teleoperation easier and more seamless. Rather than simply executing the user's input, which is hindered by the inadequacies of the interface, the robot attempts to predict the user's intent, and assists in ac-complishing it. In this work, we are interested in the scientific underpinnings of assistance: we formalize assistance under the general framework of policy blending, show how previous work methods instantiate this formalism, and provide a principled analysis of its main components: prediction of user intent and its arbitration with the user input. We define the prediction problem, with foundations in Inverse Reinforcement Learning, discuss simplifying assumptions that make it tractable, and test these on data from users teleoperating a robotic manipulator under various circumstances. We propose that arbitration should be moderated by the confidence in the prediction. Our user study analyzes the effect of the arbitration type, together with the prediction correctness and the task difficulty, on the performance of assistance and the preferences of users.
For successful deployment, personal robots must adapt to ever-changing indoor environments. While dealing with novel objects is a largely unsolved challenge in AI, it is easy for people. In this paper we present a framework for robot... more
For successful deployment, personal robots must adapt to ever-changing indoor environments. While dealing with novel objects is a largely unsolved challenge in AI, it is easy for people. In this paper we present a framework for robot supervision through Amazon Mechanical Turk. Unlike traditional models of teleoperation, people provide semantic information about the world and subjective judgements. The robot then
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
* Available as a photocopy reprint only. Allow two weeks reprinting time plus standard delivery time. No discounts or returns apply. ... Standard delivery in the US is 7 to 10 business days and outside the US delivery is 4 to 6 weeks or... more
* Available as a photocopy reprint only. Allow two weeks reprinting time plus standard delivery time. No discounts or returns apply. ... Standard delivery in the US is 7 to 10 business days and outside the US delivery is 4 to 6 weeks or longer. For further details, please see shipping policy. ... Listed below are the papers found in this volume. Click the paper title to view an abstract or to order an individual paper. ... Sign up for monthly alerts of new titles released.
We introduce a new algorithm to cover an unknown space with a homogeneous team of circular mobile robots. Our approach is based on a single robot cover-age algorithm, a boustrophedon approach, which di-vides the target two-dimensional... more
We introduce a new algorithm to cover an unknown space with a homogeneous team of circular mobile robots. Our approach is based on a single robot cover-age algorithm, a boustrophedon approach, which di-vides the target two-dimensional space into regions called cells, ...
Research Interests:
We present a planning algorithm called BiSpace that produces fast plans to complex high-dimensional problems by simultaneously exploring multiple spaces. We specifically focus on finding robust solutions to manipulation and grasp planning... more
We present a planning algorithm called BiSpace that produces fast plans to complex high-dimensional problems by simultaneously exploring multiple spaces. We specifically focus on finding robust solutions to manipulation and grasp planning problems by using BiSpace's special characteristics to explore the work and configuration spaces of the environment and robot. Furthermore, we present a number of techniques for constructing informed
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
We add to a manipulator's capabilities a new primitive motion which we term a push-grasp. While significant progress has been made in robotic grasping of objects and geometric path planning for manipulation, such work treats... more
We add to a manipulator's capabilities a new primitive motion which we term a push-grasp. While significant progress has been made in robotic grasping of objects and geometric path planning for manipulation, such work treats the world and the object being grasped as immovable, often declaring failure when simple motions of the object could produce success. We analyze the mechanics
Research Interests:
Research Interests:
Research Interests:
Research Interests: Engineering, Robotics, System Identification, Graph Theory, Oil Spill, and 16 moreWireless Network, Communication Network, Mathematical Sciences, Automatica, Connectivity, Biological systems, Observer, Reconfiguration, Decentralized Control, Sensor Array, Boolean Satisfiability, Autonomous Braking System, Graph Connectivity, Mobile Sensor Network, Time varying, and Biological System
Research Interests:
Research Interests:
AbstractWe present a sampling-based path planning al-gorithm capable of efficiently generating solutions for high-dimensional manipulation problems involving challenging inverse kinematics and complex obstacles. Our algorithm extends the... more
AbstractWe present a sampling-based path planning al-gorithm capable of efficiently generating solutions for high-dimensional manipulation problems involving challenging inverse kinematics and complex obstacles. Our algorithm extends the Rapidly-exploring Random Tree (RRT) ...
Research Interests:
Research Interests:
Research Interests:
Handing over objects to humans is an essential capability for assistive robots. While there are infinite ways to hand an object, robots should be able to choose the one that is best for the human. In this paper we focus on choosing the... more
Handing over objects to humans is an essential capability for assistive robots. While there are infinite ways to hand an object, robots should be able to choose the one that is best for the human. In this paper we focus on choosing the robot and object configuration at which the transfer of the object occurs, ie the hand-over configuration. We advocate the incorporation of user preferences in choosing hand-over configurations. We present a user study in which we collect data on human preferences and a human-robot interaction ...